Overview

Brought to you by YData

Dataset statistics

Number of variables33
Number of observations736
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory189.9 KiB
Average record size in memory264.2 B

Variable types

DateTime1
Text2
Categorical24
Numeric5
Boolean1

Alerts

Permissions has constant value "'I understand.'"Constant
Anxiety is highly overall correlated with DepressionHigh correlation
Depression is highly overall correlated with AnxietyHigh correlation
Frequency [Hip hop] is highly overall correlated with Frequency [Rap]High correlation
Frequency [Rap] is highly overall correlated with Frequency [Hip hop]High correlation
While working is highly imbalanced (51.0%)Imbalance
Composer is highly imbalanced (57.4%)Imbalance
Anxiety has 35 (4.8%) zerosZeros
Depression has 84 (11.4%) zerosZeros
Insomnia has 149 (20.2%) zerosZeros
OCD has 248 (33.7%) zerosZeros

Reproduction

Analysis started2024-11-13 13:04:08.812933
Analysis finished2024-11-13 13:04:36.084877
Duration27.27 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

Distinct735
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum2022-08-27 19:29:02
Maximum2022-11-09 01:55:20
2024-11-13T16:04:36.527125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:37.556305image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Age
Text

Distinct62
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-11-13T16:04:38.687145image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9959239
Min length1

Characters and Unicode

Total characters2941
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)2.3%

Sample

1st row18.0
2nd row63.0
3rd row18.0
4th row61.0
5th row18.0
ValueCountFrequency (%)
18.0 85
 
11.5%
19.0 61
 
8.3%
17.0 59
 
8.0%
21.0 52
 
7.1%
16.0 44
 
6.0%
20.0 40
 
5.4%
22.0 39
 
5.3%
23.0 37
 
5.0%
26.0 22
 
3.0%
25.0 22
 
3.0%
Other values (52) 275
37.4%
2024-11-13T16:04:40.030832image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 801
27.2%
. 735
25.0%
1 372
12.6%
2 341
11.6%
3 146
 
5.0%
8 112
 
3.8%
6 99
 
3.4%
7 93
 
3.2%
9 84
 
2.9%
4 84
 
2.9%
Other values (2) 74
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2941
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 801
27.2%
. 735
25.0%
1 372
12.6%
2 341
11.6%
3 146
 
5.0%
8 112
 
3.8%
6 99
 
3.4%
7 93
 
3.2%
9 84
 
2.9%
4 84
 
2.9%
Other values (2) 74
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2941
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 801
27.2%
. 735
25.0%
1 372
12.6%
2 341
11.6%
3 146
 
5.0%
8 112
 
3.8%
6 99
 
3.4%
7 93
 
3.2%
9 84
 
2.9%
4 84
 
2.9%
Other values (2) 74
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2941
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 801
27.2%
. 735
25.0%
1 372
12.6%
2 341
11.6%
3 146
 
5.0%
8 112
 
3.8%
6 99
 
3.4%
7 93
 
3.2%
9 84
 
2.9%
4 84
 
2.9%
Other values (2) 74
 
2.5%
Distinct7
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Spotify
458 
'YouTube Music'
94 
'I do not use a streaming service.'
71 
'Apple Music'
51 
'Other streaming service'
50 
Other values (2)
 
12

Length

Max length35
Median length7
Mean length12.353261
Min length1

Characters and Unicode

Total characters9092
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowSpotify
2nd rowPandora
3rd rowSpotify
4th row'YouTube Music'
5th rowSpotify

Common Values

ValueCountFrequency (%)
Spotify 458
62.2%
'YouTube Music' 94
 
12.8%
'I do not use a streaming service.' 71
 
9.6%
'Apple Music' 51
 
6.9%
'Other streaming service' 50
 
6.8%
Pandora 11
 
1.5%
? 1
 
0.1%

Length

2024-11-13T16:04:40.767898image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:41.558937image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
spotify 458
32.6%
music 145
 
10.3%
streaming 121
 
8.6%
service 121
 
8.6%
youtube 94
 
6.7%
i 71
 
5.0%
do 71
 
5.0%
not 71
 
5.0%
use 71
 
5.0%
a 71
 
5.0%
Other values (4) 113
 
8.0%

Most occurring characters

ValueCountFrequency (%)
i 845
 
9.3%
o 705
 
7.8%
t 700
 
7.7%
671
 
7.4%
e 629
 
6.9%
p 560
 
6.2%
' 532
 
5.9%
S 458
 
5.0%
f 458
 
5.0%
y 458
 
5.0%
Other values (22) 3076
33.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9092
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 845
 
9.3%
o 705
 
7.8%
t 700
 
7.7%
671
 
7.4%
e 629
 
6.9%
p 560
 
6.2%
' 532
 
5.9%
S 458
 
5.0%
f 458
 
5.0%
y 458
 
5.0%
Other values (22) 3076
33.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9092
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 845
 
9.3%
o 705
 
7.8%
t 700
 
7.7%
671
 
7.4%
e 629
 
6.9%
p 560
 
6.2%
' 532
 
5.9%
S 458
 
5.0%
f 458
 
5.0%
y 458
 
5.0%
Other values (22) 3076
33.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9092
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 845
 
9.3%
o 705
 
7.8%
t 700
 
7.7%
671
 
7.4%
e 629
 
6.9%
p 560
 
6.2%
' 532
 
5.9%
S 458
 
5.0%
f 458
 
5.0%
y 458
 
5.0%
Other values (22) 3076
33.8%

Hours per day
Real number (ℝ)

Distinct27
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5727582
Minimum0
Maximum24
Zeros6
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-11-13T16:04:42.011655image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile10
Maximum24
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.0281988
Coefficient of variation (CV)0.84758013
Kurtosis10.466149
Mean3.5727582
Median Absolute Deviation (MAD)1
Skewness2.5325429
Sum2629.55
Variance9.1699882
MonotonicityNot monotonic
2024-11-13T16:04:42.384949image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2 173
23.5%
3 120
16.3%
1 117
15.9%
4 83
11.3%
5 54
 
7.3%
6 47
 
6.4%
8 29
 
3.9%
10 20
 
2.7%
0.5 20
 
2.7%
1.5 17
 
2.3%
Other values (17) 56
 
7.6%
ValueCountFrequency (%)
0 6
 
0.8%
0.1 1
 
0.1%
0.25 3
 
0.4%
0.5 20
 
2.7%
0.7 1
 
0.1%
1 117
15.9%
1.5 17
 
2.3%
2 173
23.5%
2.5 6
 
0.8%
3 120
16.3%
ValueCountFrequency (%)
24 3
 
0.4%
20 1
 
0.1%
18 1
 
0.1%
16 1
 
0.1%
15 2
 
0.3%
14 1
 
0.1%
13 1
 
0.1%
12 9
1.2%
11 1
 
0.1%
10 20
2.7%

While working
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Yes
579 
No
154 
?
 
3

Length

Max length3
Median length3
Mean length2.7826087
Min length1

Characters and Unicode

Total characters2048
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowYes

Common Values

ValueCountFrequency (%)
Yes 579
78.7%
No 154
 
20.9%
? 3
 
0.4%

Length

2024-11-13T16:04:42.948154image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:43.531792image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
yes 579
78.7%
no 154
 
20.9%
3
 
0.4%

Most occurring characters

ValueCountFrequency (%)
Y 579
28.3%
e 579
28.3%
s 579
28.3%
N 154
 
7.5%
o 154
 
7.5%
? 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2048
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 579
28.3%
e 579
28.3%
s 579
28.3%
N 154
 
7.5%
o 154
 
7.5%
? 3
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2048
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 579
28.3%
e 579
28.3%
s 579
28.3%
N 154
 
7.5%
o 154
 
7.5%
? 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2048
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 579
28.3%
e 579
28.3%
s 579
28.3%
N 154
 
7.5%
o 154
 
7.5%
? 3
 
0.1%

Instrumentalist
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
No
497 
Yes
235 
?
 
4

Length

Max length3
Median length2
Mean length2.3138587
Min length1

Characters and Unicode

Total characters1703
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 497
67.5%
Yes 235
31.9%
? 4
 
0.5%

Length

2024-11-13T16:04:43.918069image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:44.329391image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
no 497
67.5%
yes 235
31.9%
4
 
0.5%

Most occurring characters

ValueCountFrequency (%)
N 497
29.2%
o 497
29.2%
Y 235
13.8%
e 235
13.8%
s 235
13.8%
? 4
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1703
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 497
29.2%
o 497
29.2%
Y 235
13.8%
e 235
13.8%
s 235
13.8%
? 4
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1703
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 497
29.2%
o 497
29.2%
Y 235
13.8%
e 235
13.8%
s 235
13.8%
? 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1703
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 497
29.2%
o 497
29.2%
Y 235
13.8%
e 235
13.8%
s 235
13.8%
? 4
 
0.2%

Composer
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
No
609 
Yes
126 
?
 
1

Length

Max length3
Median length2
Mean length2.169837
Min length1

Characters and Unicode

Total characters1597
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo

Common Values

ValueCountFrequency (%)
No 609
82.7%
Yes 126
 
17.1%
? 1
 
0.1%

Length

2024-11-13T16:04:44.808093image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:45.273805image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
no 609
82.7%
yes 126
 
17.1%
1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
N 609
38.1%
o 609
38.1%
Y 126
 
7.9%
e 126
 
7.9%
s 126
 
7.9%
? 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1597
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 609
38.1%
o 609
38.1%
Y 126
 
7.9%
e 126
 
7.9%
s 126
 
7.9%
? 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1597
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 609
38.1%
o 609
38.1%
Y 126
 
7.9%
e 126
 
7.9%
s 126
 
7.9%
? 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1597
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 609
38.1%
o 609
38.1%
Y 126
 
7.9%
e 126
 
7.9%
s 126
 
7.9%
? 1
 
0.1%

Fav genre
Categorical

Distinct16
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Rock
188 
Pop
114 
Metal
88 
Classical
53 
'Video game music'
44 
Other values (11)
249 

Length

Max length18
Median length9
Mean length5.5
Min length3

Characters and Unicode

Total characters4048
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLatin
2nd rowRock
3rd row'Video game music'
4th rowJazz
5th rowR&B

Common Values

ValueCountFrequency (%)
Rock 188
25.5%
Pop 114
15.5%
Metal 88
12.0%
Classical 53
 
7.2%
'Video game music' 44
 
6.0%
EDM 37
 
5.0%
R&B 35
 
4.8%
'Hip hop' 35
 
4.8%
Folk 30
 
4.1%
'K pop' 26
 
3.5%
Other values (6) 86
11.7%

Length

2024-11-13T16:04:45.739043image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
rock 188
21.2%
pop 140
15.8%
metal 88
9.9%
classical 53
 
6.0%
video 44
 
5.0%
game 44
 
5.0%
music 44
 
5.0%
edm 37
 
4.2%
hop 35
 
4.0%
hip 35
 
4.0%
Other values (9) 177
20.0%

Most occurring characters

ValueCountFrequency (%)
o 478
 
11.8%
c 285
 
7.0%
a 283
 
7.0%
p 264
 
6.5%
R 245
 
6.1%
l 230
 
5.7%
k 218
 
5.4%
' 210
 
5.2%
i 189
 
4.7%
e 182
 
4.5%
Other values (27) 1464
36.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4048
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 478
 
11.8%
c 285
 
7.0%
a 283
 
7.0%
p 264
 
6.5%
R 245
 
6.1%
l 230
 
5.7%
k 218
 
5.4%
' 210
 
5.2%
i 189
 
4.7%
e 182
 
4.5%
Other values (27) 1464
36.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4048
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 478
 
11.8%
c 285
 
7.0%
a 283
 
7.0%
p 264
 
6.5%
R 245
 
6.1%
l 230
 
5.7%
k 218
 
5.4%
' 210
 
5.2%
i 189
 
4.7%
e 182
 
4.5%
Other values (27) 1464
36.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4048
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 478
 
11.8%
c 285
 
7.0%
a 283
 
7.0%
p 264
 
6.5%
R 245
 
6.1%
l 230
 
5.7%
k 218
 
5.4%
' 210
 
5.2%
i 189
 
4.7%
e 182
 
4.5%
Other values (27) 1464
36.2%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size864.0 B
True
525 
False
211 
ValueCountFrequency (%)
True 525
71.3%
False 211
28.7%
2024-11-13T16:04:46.271233image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Yes
404 
No
328 
?
 
4

Length

Max length3
Median length3
Mean length2.5434783
Min length1

Characters and Unicode

Total characters1872
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo

Common Values

ValueCountFrequency (%)
Yes 404
54.9%
No 328
44.6%
? 4
 
0.5%

Length

2024-11-13T16:04:46.841879image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:47.475116image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
yes 404
54.9%
no 328
44.6%
4
 
0.5%

Most occurring characters

ValueCountFrequency (%)
Y 404
21.6%
e 404
21.6%
s 404
21.6%
N 328
17.5%
o 328
17.5%
? 4
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1872
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 404
21.6%
e 404
21.6%
s 404
21.6%
N 328
17.5%
o 328
17.5%
? 4
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1872
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 404
21.6%
e 404
21.6%
s 404
21.6%
N 328
17.5%
o 328
17.5%
? 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1872
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 404
21.6%
e 404
21.6%
s 404
21.6%
N 328
17.5%
o 328
17.5%
? 4
 
0.2%

BPM
Text

Distinct136
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-11-13T16:04:48.698905image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length4.2092391
Min length1

Characters and Unicode

Total characters3098
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)5.0%

Sample

1st row156.0
2nd row119.0
3rd row132.0
4th row84.0
5th row107.0
ValueCountFrequency (%)
107
 
14.5%
120.0 45
 
6.1%
140.0 25
 
3.4%
150.0 18
 
2.4%
110.0 16
 
2.2%
105.0 15
 
2.0%
130.0 13
 
1.8%
100.0 11
 
1.5%
80.0 11
 
1.5%
136.0 11
 
1.5%
Other values (126) 464
63.0%
2024-11-13T16:04:50.411125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 894
28.9%
. 629
20.3%
1 571
18.4%
2 164
 
5.3%
5 119
 
3.8%
8 119
 
3.8%
9 118
 
3.8%
? 107
 
3.5%
4 103
 
3.3%
7 93
 
3.0%
Other values (2) 181
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3098
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 894
28.9%
. 629
20.3%
1 571
18.4%
2 164
 
5.3%
5 119
 
3.8%
8 119
 
3.8%
9 118
 
3.8%
? 107
 
3.5%
4 103
 
3.3%
7 93
 
3.0%
Other values (2) 181
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3098
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 894
28.9%
. 629
20.3%
1 571
18.4%
2 164
 
5.3%
5 119
 
3.8%
8 119
 
3.8%
9 118
 
3.8%
? 107
 
3.5%
4 103
 
3.3%
7 93
 
3.0%
Other values (2) 181
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3098
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 894
28.9%
. 629
20.3%
1 571
18.4%
2 164
 
5.3%
5 119
 
3.8%
8 119
 
3.8%
9 118
 
3.8%
? 107
 
3.5%
4 103
 
3.3%
7 93
 
3.0%
Other values (2) 181
 
5.8%
Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Rarely
259 
Sometimes
200 
Never
169 
'Very frequently'
108 

Length

Max length17
Median length9
Mean length8.1997283
Min length5

Characters and Unicode

Total characters6035
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRarely
2nd rowSometimes
3rd rowNever
4th rowSometimes
5th rowNever

Common Values

ValueCountFrequency (%)
Rarely 259
35.2%
Sometimes 200
27.2%
Never 169
23.0%
'Very frequently' 108
14.7%

Length

2024-11-13T16:04:51.062010image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:51.746588image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
rarely 259
30.7%
sometimes 200
23.7%
never 169
20.0%
very 108
12.8%
frequently 108
12.8%

Most occurring characters

ValueCountFrequency (%)
e 1321
21.9%
r 644
10.7%
y 475
 
7.9%
m 400
 
6.6%
l 367
 
6.1%
t 308
 
5.1%
R 259
 
4.3%
a 259
 
4.3%
' 216
 
3.6%
s 200
 
3.3%
Other values (11) 1586
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6035
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1321
21.9%
r 644
10.7%
y 475
 
7.9%
m 400
 
6.6%
l 367
 
6.1%
t 308
 
5.1%
R 259
 
4.3%
a 259
 
4.3%
' 216
 
3.6%
s 200
 
3.3%
Other values (11) 1586
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6035
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1321
21.9%
r 644
10.7%
y 475
 
7.9%
m 400
 
6.6%
l 367
 
6.1%
t 308
 
5.1%
R 259
 
4.3%
a 259
 
4.3%
' 216
 
3.6%
s 200
 
3.3%
Other values (11) 1586
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6035
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1321
21.9%
r 644
10.7%
y 475
 
7.9%
m 400
 
6.6%
l 367
 
6.1%
t 308
 
5.1%
R 259
 
4.3%
a 259
 
4.3%
' 216
 
3.6%
s 200
 
3.3%
Other values (11) 1586
26.3%
Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
343 
Rarely
233 
Sometimes
111 
'Very frequently'
49 

Length

Max length17
Median length9
Mean length6.71875
Min length5

Characters and Unicode

Total characters4945
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd rowNever
3rd rowNever
4th rowNever
5th rowNever

Common Values

ValueCountFrequency (%)
Never 343
46.6%
Rarely 233
31.7%
Sometimes 111
 
15.1%
'Very frequently' 49
 
6.7%

Length

2024-11-13T16:04:52.457145image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:52.855899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 343
43.7%
rarely 233
29.7%
sometimes 111
 
14.1%
very 49
 
6.2%
frequently 49
 
6.2%

Most occurring characters

ValueCountFrequency (%)
e 1288
26.0%
r 674
13.6%
N 343
 
6.9%
v 343
 
6.9%
y 331
 
6.7%
l 282
 
5.7%
R 233
 
4.7%
a 233
 
4.7%
m 222
 
4.5%
t 160
 
3.2%
Other values (11) 836
16.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4945
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1288
26.0%
r 674
13.6%
N 343
 
6.9%
v 343
 
6.9%
y 331
 
6.7%
l 282
 
5.7%
R 233
 
4.7%
a 233
 
4.7%
m 222
 
4.5%
t 160
 
3.2%
Other values (11) 836
16.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4945
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1288
26.0%
r 674
13.6%
N 343
 
6.9%
v 343
 
6.9%
y 331
 
6.7%
l 282
 
5.7%
R 233
 
4.7%
a 233
 
4.7%
m 222
 
4.5%
t 160
 
3.2%
Other values (11) 836
16.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4945
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1288
26.0%
r 674
13.6%
N 343
 
6.9%
v 343
 
6.9%
y 331
 
6.7%
l 282
 
5.7%
R 233
 
4.7%
a 233
 
4.7%
m 222
 
4.5%
t 160
 
3.2%
Other values (11) 836
16.9%

Frequency [EDM]
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
307 
Rarely
194 
Sometimes
146 
'Very frequently'
89 

Length

Max length17
Median length9
Mean length7.5081522
Min length5

Characters and Unicode

Total characters5526
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRarely
2nd rowNever
3rd row'Very frequently'
4th rowNever
5th rowRarely

Common Values

ValueCountFrequency (%)
Never 307
41.7%
Rarely 194
26.4%
Sometimes 146
19.8%
'Very frequently' 89
 
12.1%

Length

2024-11-13T16:04:53.333603image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:53.851282image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 307
37.2%
rarely 194
23.5%
sometimes 146
17.7%
very 89
 
10.8%
frequently 89
 
10.8%

Most occurring characters

ValueCountFrequency (%)
e 1367
24.7%
r 679
12.3%
y 372
 
6.7%
N 307
 
5.6%
v 307
 
5.6%
m 292
 
5.3%
l 283
 
5.1%
t 235
 
4.3%
a 194
 
3.5%
R 194
 
3.5%
Other values (11) 1296
23.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5526
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1367
24.7%
r 679
12.3%
y 372
 
6.7%
N 307
 
5.6%
v 307
 
5.6%
m 292
 
5.3%
l 283
 
5.1%
t 235
 
4.3%
a 194
 
3.5%
R 194
 
3.5%
Other values (11) 1296
23.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5526
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1367
24.7%
r 679
12.3%
y 372
 
6.7%
N 307
 
5.6%
v 307
 
5.6%
m 292
 
5.3%
l 283
 
5.1%
t 235
 
4.3%
a 194
 
3.5%
R 194
 
3.5%
Other values (11) 1296
23.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5526
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1367
24.7%
r 679
12.3%
y 372
 
6.7%
N 307
 
5.6%
v 307
 
5.6%
m 292
 
5.3%
l 283
 
5.1%
t 235
 
4.3%
a 194
 
3.5%
R 194
 
3.5%
Other values (11) 1296
23.5%

Frequency [Folk]
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
292 
Rarely
221 
Sometimes
145 
'Very frequently'
78 

Length

Max length17
Median length9
Mean length7.3600543
Min length5

Characters and Unicode

Total characters5417
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd rowRarely
3rd rowNever
4th rowRarely
5th rowNever

Common Values

ValueCountFrequency (%)
Never 292
39.7%
Rarely 221
30.0%
Sometimes 145
19.7%
'Very frequently' 78
 
10.6%

Length

2024-11-13T16:04:54.381952image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:55.116498image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 292
35.9%
rarely 221
27.1%
sometimes 145
17.8%
very 78
 
9.6%
frequently 78
 
9.6%

Most occurring characters

ValueCountFrequency (%)
e 1329
24.5%
r 669
12.4%
y 377
 
7.0%
l 299
 
5.5%
N 292
 
5.4%
v 292
 
5.4%
m 290
 
5.4%
t 223
 
4.1%
a 221
 
4.1%
R 221
 
4.1%
Other values (11) 1204
22.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5417
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1329
24.5%
r 669
12.4%
y 377
 
7.0%
l 299
 
5.5%
N 292
 
5.4%
v 292
 
5.4%
m 290
 
5.4%
t 223
 
4.1%
a 221
 
4.1%
R 221
 
4.1%
Other values (11) 1204
22.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5417
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1329
24.5%
r 669
12.4%
y 377
 
7.0%
l 299
 
5.5%
N 292
 
5.4%
v 292
 
5.4%
m 290
 
5.4%
t 223
 
4.1%
a 221
 
4.1%
R 221
 
4.1%
Other values (11) 1204
22.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5417
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1329
24.5%
r 669
12.4%
y 377
 
7.0%
l 299
 
5.5%
N 292
 
5.4%
v 292
 
5.4%
m 290
 
5.4%
t 223
 
4.1%
a 221
 
4.1%
R 221
 
4.1%
Other values (11) 1204
22.2%
Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
535 
Rarely
135 
Sometimes
 
52
'Very frequently'
 
14

Length

Max length17
Median length5
Mean length5.6942935
Min length5

Characters and Unicode

Total characters4191
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd rowSometimes
3rd rowNever
4th rowSometimes
5th rowRarely

Common Values

ValueCountFrequency (%)
Never 535
72.7%
Rarely 135
 
18.3%
Sometimes 52
 
7.1%
'Very frequently' 14
 
1.9%

Length

2024-11-13T16:04:55.546023image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:55.898803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 535
71.3%
rarely 135
 
18.0%
sometimes 52
 
6.9%
very 14
 
1.9%
frequently 14
 
1.9%

Most occurring characters

ValueCountFrequency (%)
e 1351
32.2%
r 698
16.7%
N 535
 
12.8%
v 535
 
12.8%
y 163
 
3.9%
l 149
 
3.6%
R 135
 
3.2%
a 135
 
3.2%
m 104
 
2.5%
t 66
 
1.6%
Other values (11) 320
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4191
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1351
32.2%
r 698
16.7%
N 535
 
12.8%
v 535
 
12.8%
y 163
 
3.9%
l 149
 
3.6%
R 135
 
3.2%
a 135
 
3.2%
m 104
 
2.5%
t 66
 
1.6%
Other values (11) 320
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4191
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1351
32.2%
r 698
16.7%
N 535
 
12.8%
v 535
 
12.8%
y 163
 
3.9%
l 149
 
3.6%
R 135
 
3.2%
a 135
 
3.2%
m 104
 
2.5%
t 66
 
1.6%
Other values (11) 320
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4191
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1351
32.2%
r 698
16.7%
N 535
 
12.8%
v 535
 
12.8%
y 163
 
3.9%
l 149
 
3.6%
R 135
 
3.2%
a 135
 
3.2%
m 104
 
2.5%
t 66
 
1.6%
Other values (11) 320
 
7.6%

Frequency [Hip hop]
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Sometimes
218 
Rarely
214 
Never
181 
'Very frequently'
123 

Length

Max length17
Median length9
Mean length8.4809783
Min length5

Characters and Unicode

Total characters6242
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSometimes
2nd rowRarely
3rd rowRarely
4th rowNever
5th row'Very frequently'

Common Values

ValueCountFrequency (%)
Sometimes 218
29.6%
Rarely 214
29.1%
Never 181
24.6%
'Very frequently' 123
16.7%

Length

2024-11-13T16:04:56.267574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:56.672323image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
sometimes 218
25.4%
rarely 214
24.9%
never 181
21.1%
very 123
14.3%
frequently 123
14.3%

Most occurring characters

ValueCountFrequency (%)
e 1381
22.1%
r 641
 
10.3%
y 460
 
7.4%
m 436
 
7.0%
t 341
 
5.5%
l 337
 
5.4%
' 246
 
3.9%
o 218
 
3.5%
S 218
 
3.5%
s 218
 
3.5%
Other values (11) 1746
28.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6242
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1381
22.1%
r 641
 
10.3%
y 460
 
7.4%
m 436
 
7.0%
t 341
 
5.5%
l 337
 
5.4%
' 246
 
3.9%
o 218
 
3.5%
S 218
 
3.5%
s 218
 
3.5%
Other values (11) 1746
28.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6242
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1381
22.1%
r 641
 
10.3%
y 460
 
7.4%
m 436
 
7.0%
t 341
 
5.5%
l 337
 
5.4%
' 246
 
3.9%
o 218
 
3.5%
S 218
 
3.5%
s 218
 
3.5%
Other values (11) 1746
28.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6242
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1381
22.1%
r 641
 
10.3%
y 460
 
7.4%
m 436
 
7.0%
t 341
 
5.5%
l 337
 
5.4%
' 246
 
3.9%
o 218
 
3.5%
S 218
 
3.5%
s 218
 
3.5%
Other values (11) 1746
28.0%

Frequency [Jazz]
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
261 
Rarely
247 
Sometimes
175 
'Very frequently'
53 

Length

Max length17
Median length9
Mean length7.1508152
Min length5

Characters and Unicode

Total characters5263
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd row'Very frequently'
3rd rowRarely
4th row'Very frequently'
5th rowNever

Common Values

ValueCountFrequency (%)
Never 261
35.5%
Rarely 247
33.6%
Sometimes 175
23.8%
'Very frequently' 53
 
7.2%

Length

2024-11-13T16:04:57.096666image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:57.443451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 261
33.1%
rarely 247
31.3%
sometimes 175
22.2%
very 53
 
6.7%
frequently 53
 
6.7%

Most occurring characters

ValueCountFrequency (%)
e 1278
24.3%
r 614
11.7%
y 353
 
6.7%
m 350
 
6.7%
l 300
 
5.7%
N 261
 
5.0%
v 261
 
5.0%
a 247
 
4.7%
R 247
 
4.7%
t 228
 
4.3%
Other values (11) 1124
21.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5263
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1278
24.3%
r 614
11.7%
y 353
 
6.7%
m 350
 
6.7%
l 300
 
5.7%
N 261
 
5.0%
v 261
 
5.0%
a 247
 
4.7%
R 247
 
4.7%
t 228
 
4.3%
Other values (11) 1124
21.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5263
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1278
24.3%
r 614
11.7%
y 353
 
6.7%
m 350
 
6.7%
l 300
 
5.7%
N 261
 
5.0%
v 261
 
5.0%
a 247
 
4.7%
R 247
 
4.7%
t 228
 
4.3%
Other values (11) 1124
21.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5263
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1278
24.3%
r 614
11.7%
y 353
 
6.7%
m 350
 
6.7%
l 300
 
5.7%
N 261
 
5.0%
v 261
 
5.0%
a 247
 
4.7%
R 247
 
4.7%
t 228
 
4.3%
Other values (11) 1124
21.4%
Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
416 
Rarely
176 
'Very frequently'
77 
Sometimes
67 

Length

Max length17
Median length5
Mean length6.8586957
Min length5

Characters and Unicode

Total characters5048
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'Very frequently'
2nd rowRarely
3rd row'Very frequently'
4th rowSometimes
5th row'Very frequently'

Common Values

ValueCountFrequency (%)
Never 416
56.5%
Rarely 176
23.9%
'Very frequently' 77
 
10.5%
Sometimes 67
 
9.1%

Length

2024-11-13T16:04:57.855218image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:58.232316image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 416
51.2%
rarely 176
21.6%
very 77
 
9.5%
frequently 77
 
9.5%
sometimes 67
 
8.2%

Most occurring characters

ValueCountFrequency (%)
e 1373
27.2%
r 746
14.8%
N 416
 
8.2%
v 416
 
8.2%
y 330
 
6.5%
l 253
 
5.0%
R 176
 
3.5%
a 176
 
3.5%
' 154
 
3.1%
t 144
 
2.9%
Other values (11) 864
17.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5048
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1373
27.2%
r 746
14.8%
N 416
 
8.2%
v 416
 
8.2%
y 330
 
6.5%
l 253
 
5.0%
R 176
 
3.5%
a 176
 
3.5%
' 154
 
3.1%
t 144
 
2.9%
Other values (11) 864
17.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5048
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1373
27.2%
r 746
14.8%
N 416
 
8.2%
v 416
 
8.2%
y 330
 
6.5%
l 253
 
5.0%
R 176
 
3.5%
a 176
 
3.5%
' 154
 
3.1%
t 144
 
2.9%
Other values (11) 864
17.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5048
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1373
27.2%
r 746
14.8%
N 416
 
8.2%
v 416
 
8.2%
y 330
 
6.5%
l 253
 
5.0%
R 176
 
3.5%
a 176
 
3.5%
' 154
 
3.1%
t 144
 
2.9%
Other values (11) 864
17.1%
Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
443 
Rarely
172 
Sometimes
88 
'Very frequently'
 
33

Length

Max length17
Median length5
Mean length6.25
Min length5

Characters and Unicode

Total characters4600
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'Very frequently'
2nd rowSometimes
3rd rowNever
4th row'Very frequently'
5th rowSometimes

Common Values

ValueCountFrequency (%)
Never 443
60.2%
Rarely 172
 
23.4%
Sometimes 88
 
12.0%
'Very frequently' 33
 
4.5%

Length

2024-11-13T16:04:58.696059image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:04:59.030383image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 443
57.6%
rarely 172
 
22.4%
sometimes 88
 
11.4%
very 33
 
4.3%
frequently 33
 
4.3%

Most occurring characters

ValueCountFrequency (%)
e 1333
29.0%
r 681
14.8%
N 443
 
9.6%
v 443
 
9.6%
y 238
 
5.2%
l 205
 
4.5%
m 176
 
3.8%
a 172
 
3.7%
R 172
 
3.7%
t 121
 
2.6%
Other values (11) 616
13.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4600
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1333
29.0%
r 681
14.8%
N 443
 
9.6%
v 443
 
9.6%
y 238
 
5.2%
l 205
 
4.5%
m 176
 
3.8%
a 172
 
3.7%
R 172
 
3.7%
t 121
 
2.6%
Other values (11) 616
13.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4600
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1333
29.0%
r 681
14.8%
N 443
 
9.6%
v 443
 
9.6%
y 238
 
5.2%
l 205
 
4.5%
m 176
 
3.8%
a 172
 
3.7%
R 172
 
3.7%
t 121
 
2.6%
Other values (11) 616
13.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4600
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1333
29.0%
r 681
14.8%
N 443
 
9.6%
v 443
 
9.6%
y 238
 
5.2%
l 205
 
4.5%
m 176
 
3.8%
a 172
 
3.7%
R 172
 
3.7%
t 121
 
2.6%
Other values (11) 616
13.4%

Frequency [Lofi]
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
280 
Rarely
211 
Sometimes
160 
'Very frequently'
85 

Length

Max length17
Median length9
Mean length7.5421196
Min length5

Characters and Unicode

Total characters5551
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRarely
2nd rowRarely
3rd rowSometimes
4th rowSometimes
5th rowSometimes

Common Values

ValueCountFrequency (%)
Never 280
38.0%
Rarely 211
28.7%
Sometimes 160
21.7%
'Very frequently' 85
 
11.5%

Length

2024-11-13T16:04:59.772463image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:00.687600image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 280
34.1%
rarely 211
25.7%
sometimes 160
19.5%
very 85
 
10.4%
frequently 85
 
10.4%

Most occurring characters

ValueCountFrequency (%)
e 1346
24.2%
r 661
11.9%
y 381
 
6.9%
m 320
 
5.8%
l 296
 
5.3%
N 280
 
5.0%
v 280
 
5.0%
t 245
 
4.4%
a 211
 
3.8%
R 211
 
3.8%
Other values (11) 1320
23.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5551
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1346
24.2%
r 661
11.9%
y 381
 
6.9%
m 320
 
5.8%
l 296
 
5.3%
N 280
 
5.0%
v 280
 
5.0%
t 245
 
4.4%
a 211
 
3.8%
R 211
 
3.8%
Other values (11) 1320
23.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5551
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1346
24.2%
r 661
11.9%
y 381
 
6.9%
m 320
 
5.8%
l 296
 
5.3%
N 280
 
5.0%
v 280
 
5.0%
t 245
 
4.4%
a 211
 
3.8%
R 211
 
3.8%
Other values (11) 1320
23.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5551
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1346
24.2%
r 661
11.9%
y 381
 
6.9%
m 320
 
5.8%
l 296
 
5.3%
N 280
 
5.0%
v 280
 
5.0%
t 245
 
4.4%
a 211
 
3.8%
R 211
 
3.8%
Other values (11) 1320
23.8%
Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
264 
Rarely
192 
'Very frequently'
146 
Sometimes
134 

Length

Max length17
Median length9
Mean length8.3695652
Min length5

Characters and Unicode

Total characters6160
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd rowNever
3rd rowSometimes
4th rowNever
5th rowNever

Common Values

ValueCountFrequency (%)
Never 264
35.9%
Rarely 192
26.1%
'Very frequently' 146
19.8%
Sometimes 134
18.2%

Length

2024-11-13T16:05:01.203076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:01.544865image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 264
29.9%
rarely 192
21.8%
very 146
16.6%
frequently 146
16.6%
sometimes 134
15.2%

Most occurring characters

ValueCountFrequency (%)
e 1426
23.1%
r 748
12.1%
y 484
 
7.9%
l 338
 
5.5%
' 292
 
4.7%
t 280
 
4.5%
m 268
 
4.4%
N 264
 
4.3%
v 264
 
4.3%
R 192
 
3.1%
Other values (11) 1604
26.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6160
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1426
23.1%
r 748
12.1%
y 484
 
7.9%
l 338
 
5.5%
' 292
 
4.7%
t 280
 
4.5%
m 268
 
4.4%
N 264
 
4.3%
v 264
 
4.3%
R 192
 
3.1%
Other values (11) 1604
26.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6160
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1426
23.1%
r 748
12.1%
y 484
 
7.9%
l 338
 
5.5%
' 292
 
4.7%
t 280
 
4.5%
m 268
 
4.4%
N 264
 
4.3%
v 264
 
4.3%
R 192
 
3.1%
Other values (11) 1604
26.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6160
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1426
23.1%
r 748
12.1%
y 484
 
7.9%
l 338
 
5.5%
' 292
 
4.7%
t 280
 
4.5%
m 268
 
4.4%
N 264
 
4.3%
v 264
 
4.3%
R 192
 
3.1%
Other values (11) 1604
26.0%

Frequency [Pop]
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
'Very frequently'
277 
Sometimes
261 
Rarely
142 
Never
56 

Length

Max length17
Median length9
Mean length11.127717
Min length5

Characters and Unicode

Total characters8190
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'Very frequently'
2nd rowSometimes
3rd rowRarely
4th rowSometimes
5th rowSometimes

Common Values

ValueCountFrequency (%)
'Very frequently' 277
37.6%
Sometimes 261
35.5%
Rarely 142
19.3%
Never 56
 
7.6%

Length

2024-11-13T16:05:02.020571image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:02.423321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
very 277
27.3%
frequently 277
27.3%
sometimes 261
25.8%
rarely 142
14.0%
never 56
 
5.5%

Most occurring characters

ValueCountFrequency (%)
e 1607
19.6%
r 752
 
9.2%
y 696
 
8.5%
' 554
 
6.8%
t 538
 
6.6%
m 522
 
6.4%
l 419
 
5.1%
277
 
3.4%
f 277
 
3.4%
q 277
 
3.4%
Other values (11) 2271
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8190
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1607
19.6%
r 752
 
9.2%
y 696
 
8.5%
' 554
 
6.8%
t 538
 
6.6%
m 522
 
6.4%
l 419
 
5.1%
277
 
3.4%
f 277
 
3.4%
q 277
 
3.4%
Other values (11) 2271
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8190
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1607
19.6%
r 752
 
9.2%
y 696
 
8.5%
' 554
 
6.8%
t 538
 
6.6%
m 522
 
6.4%
l 419
 
5.1%
277
 
3.4%
f 277
 
3.4%
q 277
 
3.4%
Other values (11) 2271
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8190
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1607
19.6%
r 752
 
9.2%
y 696
 
8.5%
' 554
 
6.8%
t 538
 
6.6%
m 522
 
6.4%
l 419
 
5.1%
277
 
3.4%
f 277
 
3.4%
q 277
 
3.4%
Other values (11) 2271
27.7%

Frequency [R&B]
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
225 
Rarely
211 
Sometimes
184 
'Very frequently'
116 

Length

Max length17
Median length9
Mean length8.1779891
Min length5

Characters and Unicode

Total characters6019
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSometimes
2nd rowSometimes
3rd rowNever
4th rowSometimes
5th row'Very frequently'

Common Values

ValueCountFrequency (%)
Never 225
30.6%
Rarely 211
28.7%
Sometimes 184
25.0%
'Very frequently' 116
15.8%

Length

2024-11-13T16:05:02.916015image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:03.325362image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 225
26.4%
rarely 211
24.8%
sometimes 184
21.6%
very 116
13.6%
frequently 116
13.6%

Most occurring characters

ValueCountFrequency (%)
e 1377
22.9%
r 668
11.1%
y 443
 
7.4%
m 368
 
6.1%
l 327
 
5.4%
t 300
 
5.0%
' 232
 
3.9%
N 225
 
3.7%
v 225
 
3.7%
a 211
 
3.5%
Other values (11) 1643
27.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6019
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1377
22.9%
r 668
11.1%
y 443
 
7.4%
m 368
 
6.1%
l 327
 
5.4%
t 300
 
5.0%
' 232
 
3.9%
N 225
 
3.7%
v 225
 
3.7%
a 211
 
3.5%
Other values (11) 1643
27.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6019
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1377
22.9%
r 668
11.1%
y 443
 
7.4%
m 368
 
6.1%
l 327
 
5.4%
t 300
 
5.0%
' 232
 
3.9%
N 225
 
3.7%
v 225
 
3.7%
a 211
 
3.5%
Other values (11) 1643
27.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6019
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1377
22.9%
r 668
11.1%
y 443
 
7.4%
m 368
 
6.1%
l 327
 
5.4%
t 300
 
5.0%
' 232
 
3.9%
N 225
 
3.7%
v 225
 
3.7%
a 211
 
3.5%
Other values (11) 1643
27.3%

Frequency [Rap]
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Rarely
215 
Never
200 
Sometimes
195 
'Very frequently'
126 

Length

Max length17
Median length9
Mean length8.40625
Min length5

Characters and Unicode

Total characters6187
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'Very frequently'
2nd rowRarely
3rd rowRarely
4th rowNever
5th row'Very frequently'

Common Values

ValueCountFrequency (%)
Rarely 215
29.2%
Never 200
27.2%
Sometimes 195
26.5%
'Very frequently' 126
17.1%

Length

2024-11-13T16:05:03.964495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:04.384765image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
rarely 215
24.9%
never 200
23.2%
sometimes 195
22.6%
very 126
14.6%
frequently 126
14.6%

Most occurring characters

ValueCountFrequency (%)
e 1383
22.4%
r 667
 
10.8%
y 467
 
7.5%
m 390
 
6.3%
l 341
 
5.5%
t 321
 
5.2%
' 252
 
4.1%
a 215
 
3.5%
R 215
 
3.5%
v 200
 
3.2%
Other values (11) 1736
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6187
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1383
22.4%
r 667
 
10.8%
y 467
 
7.5%
m 390
 
6.3%
l 341
 
5.5%
t 321
 
5.2%
' 252
 
4.1%
a 215
 
3.5%
R 215
 
3.5%
v 200
 
3.2%
Other values (11) 1736
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6187
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1383
22.4%
r 667
 
10.8%
y 467
 
7.5%
m 390
 
6.3%
l 341
 
5.5%
t 321
 
5.2%
' 252
 
4.1%
a 215
 
3.5%
R 215
 
3.5%
v 200
 
3.2%
Other values (11) 1736
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6187
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1383
22.4%
r 667
 
10.8%
y 467
 
7.5%
m 390
 
6.3%
l 341
 
5.5%
t 321
 
5.2%
' 252
 
4.1%
a 215
 
3.5%
R 215
 
3.5%
v 200
 
3.2%
Other values (11) 1736
28.1%

Frequency [Rock]
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
'Very frequently'
330 
Sometimes
219 
Rarely
96 
Never
91 

Length

Max length17
Median length9
Mean length11.701087
Min length5

Characters and Unicode

Total characters8612
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd row'Very frequently'
3rd rowRarely
4th rowNever
5th rowNever

Common Values

ValueCountFrequency (%)
'Very frequently' 330
44.8%
Sometimes 219
29.8%
Rarely 96
 
13.0%
Never 91
 
12.4%

Length

2024-11-13T16:05:04.892082image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:05.373313image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
very 330
31.0%
frequently 330
31.0%
sometimes 219
20.5%
rarely 96
 
9.0%
never 91
 
8.5%

Most occurring characters

ValueCountFrequency (%)
e 1706
19.8%
r 847
 
9.8%
y 756
 
8.8%
' 660
 
7.7%
t 549
 
6.4%
m 438
 
5.1%
l 426
 
4.9%
330
 
3.8%
f 330
 
3.8%
q 330
 
3.8%
Other values (11) 2240
26.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8612
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1706
19.8%
r 847
 
9.8%
y 756
 
8.8%
' 660
 
7.7%
t 549
 
6.4%
m 438
 
5.1%
l 426
 
4.9%
330
 
3.8%
f 330
 
3.8%
q 330
 
3.8%
Other values (11) 2240
26.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8612
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1706
19.8%
r 847
 
9.8%
y 756
 
8.8%
' 660
 
7.7%
t 549
 
6.4%
m 438
 
5.1%
l 426
 
4.9%
330
 
3.8%
f 330
 
3.8%
q 330
 
3.8%
Other values (11) 2240
26.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8612
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1706
19.8%
r 847
 
9.8%
y 756
 
8.8%
' 660
 
7.7%
t 549
 
6.4%
m 438
 
5.1%
l 426
 
4.9%
330
 
3.8%
f 330
 
3.8%
q 330
 
3.8%
Other values (11) 2240
26.0%
Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Never
236 
Rarely
197 
Sometimes
186 
'Very frequently'
117 

Length

Max length17
Median length9
Mean length8.1861413
Min length5

Characters and Unicode

Total characters6025
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSometimes
2nd rowRarely
3rd row'Very frequently'
4th rowNever
5th rowRarely

Common Values

ValueCountFrequency (%)
Never 236
32.1%
Rarely 197
26.8%
Sometimes 186
25.3%
'Very frequently' 117
15.9%

Length

2024-11-13T16:05:05.782062image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:06.139839image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
never 236
27.7%
rarely 197
23.1%
sometimes 186
21.8%
very 117
13.7%
frequently 117
13.7%

Most occurring characters

ValueCountFrequency (%)
e 1392
23.1%
r 667
11.1%
y 431
 
7.2%
m 372
 
6.2%
l 314
 
5.2%
t 303
 
5.0%
N 236
 
3.9%
v 236
 
3.9%
' 234
 
3.9%
a 197
 
3.3%
Other values (11) 1643
27.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6025
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1392
23.1%
r 667
11.1%
y 431
 
7.2%
m 372
 
6.2%
l 314
 
5.2%
t 303
 
5.0%
N 236
 
3.9%
v 236
 
3.9%
' 234
 
3.9%
a 197
 
3.3%
Other values (11) 1643
27.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6025
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1392
23.1%
r 667
11.1%
y 431
 
7.2%
m 372
 
6.2%
l 314
 
5.2%
t 303
 
5.0%
N 236
 
3.9%
v 236
 
3.9%
' 234
 
3.9%
a 197
 
3.3%
Other values (11) 1643
27.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6025
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1392
23.1%
r 667
11.1%
y 431
 
7.2%
m 372
 
6.2%
l 314
 
5.2%
t 303
 
5.0%
N 236
 
3.9%
v 236
 
3.9%
' 234
 
3.9%
a 197
 
3.3%
Other values (11) 1643
27.3%

Anxiety
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8376359
Minimum0
Maximum10
Zeros35
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-11-13T16:05:06.642059image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median6
Q38
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.7930544
Coefficient of variation (CV)0.47845643
Kurtosis-0.76579107
Mean5.8376359
Median Absolute Deviation (MAD)2
Skewness-0.42134997
Sum4296.5
Variance7.801153
MonotonicityNot monotonic
2024-11-13T16:05:07.062798image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 122
16.6%
8 115
15.6%
6 83
11.3%
3 69
9.4%
10 67
9.1%
5 59
8.0%
9 56
7.6%
4 56
7.6%
2 44
 
6.0%
0 35
 
4.8%
Other values (2) 30
 
4.1%
ValueCountFrequency (%)
0 35
 
4.8%
1 29
 
3.9%
2 44
 
6.0%
3 69
9.4%
4 56
7.6%
5 59
8.0%
6 83
11.3%
7 122
16.6%
7.5 1
 
0.1%
8 115
15.6%
ValueCountFrequency (%)
10 67
9.1%
9 56
7.6%
8 115
15.6%
7.5 1
 
0.1%
7 122
16.6%
6 83
11.3%
5 59
8.0%
4 56
7.6%
3 69
9.4%
2 44
 
6.0%

Depression
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7961957
Minimum0
Maximum10
Zeros84
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-11-13T16:05:07.521041image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q37
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.02887
Coefficient of variation (CV)0.63151511
Kurtosis-1.1459474
Mean4.7961957
Median Absolute Deviation (MAD)3
Skewness-0.048448873
Sum3530
Variance9.1740535
MonotonicityNot monotonic
2024-11-13T16:05:08.109674image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 96
13.0%
2 93
12.6%
6 88
12.0%
0 84
11.4%
8 77
10.5%
3 59
8.0%
4 58
7.9%
5 56
7.6%
10 45
6.1%
1 40
5.4%
Other values (2) 40
5.4%
ValueCountFrequency (%)
0 84
11.4%
1 40
5.4%
2 93
12.6%
3 59
8.0%
3.5 2
 
0.3%
4 58
7.9%
5 56
7.6%
6 88
12.0%
7 96
13.0%
8 77
10.5%
ValueCountFrequency (%)
10 45
6.1%
9 38
 
5.2%
8 77
10.5%
7 96
13.0%
6 88
12.0%
5 56
7.6%
4 58
7.9%
3.5 2
 
0.3%
3 59
8.0%
2 93
12.6%

Insomnia
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7384511
Minimum0
Maximum10
Zeros149
Zeros (%)20.2%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-11-13T16:05:08.489623image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile9
Maximum10
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0886894
Coefficient of variation (CV)0.82619496
Kurtosis-1.0212724
Mean3.7384511
Median Absolute Deviation (MAD)3
Skewness0.41645538
Sum2751.5
Variance9.5400025
MonotonicityNot monotonic
2024-11-13T16:05:08.914361image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 149
20.2%
2 88
12.0%
1 82
11.1%
3 68
9.2%
6 62
8.4%
7 59
 
8.0%
4 59
 
8.0%
5 58
 
7.9%
8 49
 
6.7%
10 34
 
4.6%
Other values (2) 28
 
3.8%
ValueCountFrequency (%)
0 149
20.2%
1 82
11.1%
2 88
12.0%
3 68
9.2%
3.5 1
 
0.1%
4 59
 
8.0%
5 58
 
7.9%
6 62
8.4%
7 59
 
8.0%
8 49
 
6.7%
ValueCountFrequency (%)
10 34
 
4.6%
9 27
 
3.7%
8 49
6.7%
7 59
8.0%
6 62
8.4%
5 58
7.9%
4 59
8.0%
3.5 1
 
0.1%
3 68
9.2%
2 88
12.0%

OCD
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6372283
Minimum0
Maximum10
Zeros248
Zeros (%)33.7%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-11-13T16:05:09.472014image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile8
Maximum10
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.8420171
Coefficient of variation (CV)1.0776531
Kurtosis-0.12732389
Mean2.6372283
Median Absolute Deviation (MAD)2
Skewness0.95429085
Sum1941
Variance8.0770612
MonotonicityNot monotonic
2024-11-13T16:05:09.906288image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 248
33.7%
2 96
 
13.0%
1 95
 
12.9%
3 64
 
8.7%
5 54
 
7.3%
4 48
 
6.5%
7 34
 
4.6%
6 33
 
4.5%
8 28
 
3.8%
10 20
 
2.7%
Other values (3) 16
 
2.2%
ValueCountFrequency (%)
0 248
33.7%
1 95
 
12.9%
2 96
 
13.0%
3 64
 
8.7%
4 48
 
6.5%
5 54
 
7.3%
5.5 1
 
0.1%
6 33
 
4.5%
7 34
 
4.6%
8 28
 
3.8%
ValueCountFrequency (%)
10 20
 
2.7%
9 14
 
1.9%
8.5 1
 
0.1%
8 28
3.8%
7 34
4.6%
6 33
4.5%
5.5 1
 
0.1%
5 54
7.3%
4 48
6.5%
3 64
8.7%

Music effects
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Improve
542 
'No effect'
169 
Worsen
 
17
?
 
8

Length

Max length11
Median length7
Mean length7.830163
Min length1

Characters and Unicode

Total characters5763
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row?
2nd row?
3rd row'No effect'
4th rowImprove
5th rowImprove

Common Values

ValueCountFrequency (%)
Improve 542
73.6%
'No effect' 169
 
23.0%
Worsen 17
 
2.3%
? 8
 
1.1%

Length

2024-11-13T16:05:10.443480image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:11.075088image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
improve 542
59.9%
no 169
 
18.7%
effect 169
 
18.7%
worsen 17
 
1.9%
8
 
0.9%

Most occurring characters

ValueCountFrequency (%)
e 897
15.6%
o 728
12.6%
r 559
9.7%
I 542
9.4%
p 542
9.4%
v 542
9.4%
m 542
9.4%
' 338
 
5.9%
f 338
 
5.9%
c 169
 
2.9%
Other values (7) 566
9.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5763
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 897
15.6%
o 728
12.6%
r 559
9.7%
I 542
9.4%
p 542
9.4%
v 542
9.4%
m 542
9.4%
' 338
 
5.9%
f 338
 
5.9%
c 169
 
2.9%
Other values (7) 566
9.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5763
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 897
15.6%
o 728
12.6%
r 559
9.7%
I 542
9.4%
p 542
9.4%
v 542
9.4%
m 542
9.4%
' 338
 
5.9%
f 338
 
5.9%
c 169
 
2.9%
Other values (7) 566
9.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5763
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 897
15.6%
o 728
12.6%
r 559
9.7%
I 542
9.4%
p 542
9.4%
v 542
9.4%
m 542
9.4%
' 338
 
5.9%
f 338
 
5.9%
c 169
 
2.9%
Other values (7) 566
9.8%

Permissions
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
'I understand.'
736 

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters11040
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'I understand.'
2nd row'I understand.'
3rd row'I understand.'
4th row'I understand.'
5th row'I understand.'

Common Values

ValueCountFrequency (%)
'I understand.' 736
100.0%

Length

2024-11-13T16:05:11.452104image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-13T16:05:12.061745image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
i 736
50.0%
understand 736
50.0%

Most occurring characters

ValueCountFrequency (%)
' 1472
13.3%
n 1472
13.3%
d 1472
13.3%
I 736
6.7%
736
6.7%
u 736
6.7%
e 736
6.7%
r 736
6.7%
s 736
6.7%
t 736
6.7%
Other values (2) 1472
13.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11040
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 1472
13.3%
n 1472
13.3%
d 1472
13.3%
I 736
6.7%
736
6.7%
u 736
6.7%
e 736
6.7%
r 736
6.7%
s 736
6.7%
t 736
6.7%
Other values (2) 1472
13.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11040
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 1472
13.3%
n 1472
13.3%
d 1472
13.3%
I 736
6.7%
736
6.7%
u 736
6.7%
e 736
6.7%
r 736
6.7%
s 736
6.7%
t 736
6.7%
Other values (2) 1472
13.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11040
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 1472
13.3%
n 1472
13.3%
d 1472
13.3%
I 736
6.7%
736
6.7%
u 736
6.7%
e 736
6.7%
r 736
6.7%
s 736
6.7%
t 736
6.7%
Other values (2) 1472
13.3%

Interactions

2024-11-13T16:04:30.212014image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:20.749171image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:22.462646image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:25.791597image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:28.495763image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:30.699712image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:21.099956image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:23.509033image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:26.317272image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:28.821560image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:31.072007image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:21.412760image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:24.117410image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:27.388448image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:29.281276image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:31.406800image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:21.751551image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:24.825671image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:27.750225image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:29.583615image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:31.971977image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:22.130851image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:25.420827image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:28.147978image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-13T16:04:29.878685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-11-13T16:05:12.617602image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
AnxietyComposerDepressionExploratoryFav genreForeign languagesFrequency [Classical]Frequency [Country]Frequency [EDM]Frequency [Folk]Frequency [Gospel]Frequency [Hip hop]Frequency [Jazz]Frequency [K pop]Frequency [Latin]Frequency [Lofi]Frequency [Metal]Frequency [Pop]Frequency [R&B]Frequency [Rap]Frequency [Rock]Frequency [Video game music]Hours per dayInsomniaInstrumentalistMusic effectsOCDPrimary streaming serviceWhile working
Anxiety1.0000.0000.5120.0000.0510.0880.0000.0410.0580.0000.0730.0340.0000.0000.0490.0830.0840.1000.0000.0630.0560.0750.0940.2940.0000.0830.3430.0000.084
Composer0.0001.0000.0000.0850.1320.3510.0470.0350.0000.0320.0330.0520.1300.0680.0000.0000.0650.0000.0000.0140.0000.0000.0650.0000.4510.2490.0420.0000.407
Depression0.5120.0001.0000.0740.0390.0490.0000.0000.0610.0800.0000.0850.0440.0000.0000.0810.1160.0410.0530.0980.0870.0940.1350.3860.0000.1200.2080.0440.051
Exploratory0.0000.0850.0741.0000.1940.1740.0520.0000.1210.1250.0770.2240.1610.1680.0690.2450.1410.1890.1700.2490.1520.1000.1490.0000.0520.1480.0720.2710.130
Fav genre0.0510.1320.0390.1941.0000.1630.3760.4200.3700.3120.3230.3680.3060.3800.2160.2480.4440.3110.3220.3470.3660.2980.0790.0550.2210.1570.0000.1390.113
Foreign languages0.0880.3510.0490.1740.1631.0000.0890.0000.1470.0540.0000.0980.0510.2240.1490.1360.0490.1040.0880.1370.0000.1420.0550.0610.1760.1040.0660.0990.219
Frequency [Classical]0.0000.0470.0000.0520.3760.0891.0000.1120.0770.1190.0950.0690.1990.0230.0870.0640.0750.0720.0920.1090.1160.0630.0000.0810.1830.0000.0000.0000.000
Frequency [Country]0.0410.0350.0000.0000.4200.0000.1121.0000.0440.2140.1730.0820.0990.0940.1160.0990.0900.0390.0960.0840.1350.0740.0000.0190.0180.0000.0540.0900.057
Frequency [EDM]0.0580.0000.0610.1210.3700.1470.0770.0441.0000.0430.0600.1710.0590.1600.0730.1660.0640.0910.1110.1530.0720.1500.0820.0500.0470.0460.0890.0430.092
Frequency [Folk]0.0000.0320.0800.1250.3120.0540.1190.2140.0431.0000.1260.0520.0890.1000.1040.0760.1630.0680.0630.0150.2070.0450.0390.0000.0000.0000.0000.0370.000
Frequency [Gospel]0.0730.0330.0000.0770.3230.0000.0950.1730.0600.1261.0000.0870.1370.0540.1380.0710.0540.0000.1510.0780.0500.0500.0000.0660.0270.0550.0000.1360.000
Frequency [Hip hop]0.0340.0520.0850.2240.3680.0980.0690.0820.1710.0520.0871.0000.1470.1620.1380.1850.0280.1870.3300.5880.0720.0770.0880.0390.1130.0380.0000.1130.000
Frequency [Jazz]0.0000.1300.0440.1610.3060.0510.1990.0990.0590.0890.1370.1471.0000.0680.1900.1500.0740.0760.2020.0890.1000.0880.0500.0360.1280.0000.0160.0470.054
Frequency [K pop]0.0000.0680.0000.1680.3800.2240.0230.0940.1600.1000.0540.1620.0681.0000.1790.1590.1030.1970.2060.1660.1130.0910.0750.0000.0520.0740.0420.0720.131
Frequency [Latin]0.0490.0000.0000.0690.2160.1490.0870.1160.0730.1040.1380.1380.1900.1791.0000.1040.0450.1030.2240.1300.0680.0000.0920.0250.0000.0080.0000.0610.076
Frequency [Lofi]0.0830.0000.0810.2450.2480.1360.0640.0990.1660.0760.0710.1850.1500.1590.1041.0000.0670.1540.1520.1500.0000.2090.0850.0000.0000.0050.0270.1060.143
Frequency [Metal]0.0840.0650.1160.1410.4440.0490.0750.0900.0640.1630.0540.0280.0740.1030.0450.0671.0000.1030.1280.0630.3220.1160.0770.0780.0000.0000.0000.0440.032
Frequency [Pop]0.1000.0000.0410.1890.3110.1040.0720.0390.0910.0680.0000.1870.0760.1970.1030.1540.1031.0000.2370.1660.0730.0000.0380.0000.0630.0430.0430.0830.040
Frequency [R&B]0.0000.0000.0530.1700.3220.0880.0920.0960.1110.0630.1510.3300.2020.2060.2240.1520.1280.2371.0000.3340.1100.0190.0920.0440.0890.0870.0970.0750.065
Frequency [Rap]0.0630.0140.0980.2490.3470.1370.1090.0840.1530.0150.0780.5880.0890.1660.1300.1500.0630.1660.3341.0000.0900.0210.0850.0380.0990.0000.0000.1160.054
Frequency [Rock]0.0560.0000.0870.1520.3660.0000.1160.1350.0720.2070.0500.0720.1000.1130.0680.0000.3220.0730.1100.0901.0000.0670.0000.0310.0490.0000.0610.0520.000
Frequency [Video game music]0.0750.0000.0940.1000.2980.1420.0630.0740.1500.0450.0500.0770.0880.0910.0000.2090.1160.0000.0190.0210.0671.0000.0290.0550.0670.0000.0000.0710.088
Hours per day0.0940.0650.1350.1490.0790.0550.0000.0000.0820.0390.0000.0880.0500.0750.0920.0850.0770.0380.0920.0850.0000.0291.0000.1480.0000.0000.1250.0000.355
Insomnia0.2940.0000.3860.0000.0550.0610.0810.0190.0500.0000.0660.0390.0360.0000.0250.0000.0780.0000.0440.0380.0310.0550.1481.0000.0000.0000.2410.0560.126
Instrumentalist0.0000.4510.0000.0520.2210.1760.1830.0180.0470.0000.0270.1130.1280.0520.0000.0000.0000.0630.0890.0990.0490.0670.0000.0001.0000.1270.0000.0000.206
Music effects0.0830.2490.1200.1480.1570.1040.0000.0000.0460.0000.0550.0380.0000.0740.0080.0050.0000.0430.0870.0000.0000.0000.0000.0000.1271.0000.0000.0250.175
OCD0.3430.0420.2080.0720.0000.0660.0000.0540.0890.0000.0000.0000.0160.0420.0000.0270.0000.0430.0970.0000.0610.0000.1250.2410.0000.0001.0000.0330.071
Primary streaming service0.0000.0000.0440.2710.1390.0990.0000.0900.0430.0370.1360.1130.0470.0720.0610.1060.0440.0830.0750.1160.0520.0710.0000.0560.0000.0250.0331.0000.010
While working0.0840.4070.0510.1300.1130.2190.0000.0570.0920.0000.0000.0000.0540.1310.0760.1430.0320.0400.0650.0540.0000.0880.3550.1260.2060.1750.0710.0101.000

Missing values

2024-11-13T16:04:32.864103image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-13T16:04:35.453742image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampAgePrimary streaming serviceHours per dayWhile workingInstrumentalistComposerFav genreExploratoryForeign languagesBPMFrequency [Classical]Frequency [Country]Frequency [EDM]Frequency [Folk]Frequency [Gospel]Frequency [Hip hop]Frequency [Jazz]Frequency [K pop]Frequency [Latin]Frequency [Lofi]Frequency [Metal]Frequency [Pop]Frequency [R&B]Frequency [Rap]Frequency [Rock]Frequency [Video game music]AnxietyDepressionInsomniaOCDMusic effectsPermissions
0'8/27/2022 19:29:02'18.0Spotify3.0YesYesYesLatinYesYes156.0RarelyNeverRarelyNeverNeverSometimesNever'Very frequently''Very frequently'RarelyNever'Very frequently'Sometimes'Very frequently'NeverSometimes3.00.01.00.0?'I understand.'
1'8/27/2022 19:57:31'63.0Pandora1.5YesNoNoRockYesNo119.0SometimesNeverNeverRarelySometimesRarely'Very frequently'RarelySometimesRarelyNeverSometimesSometimesRarely'Very frequently'Rarely7.02.02.01.0?'I understand.'
2'8/27/2022 21:28:18'18.0Spotify4.0NoNoNo'Video game music'NoYes132.0NeverNever'Very frequently'NeverNeverRarelyRarely'Very frequently'NeverSometimesSometimesRarelyNeverRarelyRarely'Very frequently'7.07.010.02.0'No effect''I understand.'
3'8/27/2022 21:40:40'61.0'YouTube Music'2.5YesNoYesJazzYesYes84.0SometimesNeverNeverRarelySometimesNever'Very frequently'Sometimes'Very frequently'SometimesNeverSometimesSometimesNeverNeverNever9.07.03.03.0Improve'I understand.'
4'8/27/2022 21:54:47'18.0Spotify4.0YesNoNoR&BYesNo107.0NeverNeverRarelyNeverRarely'Very frequently'Never'Very frequently'SometimesSometimesNeverSometimes'Very frequently''Very frequently'NeverRarely7.02.05.09.0Improve'I understand.'
5'8/27/2022 21:56:50'18.0Spotify5.0YesYesYesJazzYesYes86.0RarelySometimesNeverNeverNeverSometimes'Very frequently''Very frequently'Rarely'Very frequently'Rarely'Very frequently''Very frequently''Very frequently''Very frequently'Never8.08.07.07.0Improve'I understand.'
6'8/27/2022 22:00:29'18.0'YouTube Music'3.0YesYesNo'Video game music'YesYes66.0SometimesNeverRarelySometimesRarelyRarelySometimesNeverRarelyRarelyRarelyRarelyRarelyNeverNeverSometimes4.08.06.00.0Improve'I understand.'
7'8/27/2022 22:18:59'21.0Spotify1.0YesNoNo'K pop'YesYes95.0NeverNeverRarelyNeverNever'Very frequently'Rarely'Very frequently'NeverSometimesNeverSometimesSometimesRarelyNeverRarely5.03.05.03.0Improve'I understand.'
8'8/27/2022 22:33:05'19.0Spotify6.0YesNoNoRockNoNo94.0Never'Very frequently'NeverSometimesNeverNeverNeverNeverNeverNever'Very frequently'NeverNeverNever'Very frequently'Never2.00.00.00.0Improve'I understand.'
9'8/27/2022 22:44:03'18.0'I do not use a streaming service.'1.0YesNoNoR&BYesYes155.0RarelyRarelyRarelyRarelySometimesRarelyRarelyNeverRarelyRarelyNeverSometimesSometimesRarelySometimesSometimes2.02.05.01.0Improve'I understand.'
TimestampAgePrimary streaming serviceHours per dayWhile workingInstrumentalistComposerFav genreExploratoryForeign languagesBPMFrequency [Classical]Frequency [Country]Frequency [EDM]Frequency [Folk]Frequency [Gospel]Frequency [Hip hop]Frequency [Jazz]Frequency [K pop]Frequency [Latin]Frequency [Lofi]Frequency [Metal]Frequency [Pop]Frequency [R&B]Frequency [Rap]Frequency [Rock]Frequency [Video game music]AnxietyDepressionInsomniaOCDMusic effectsPermissions
726'10/23/2022 20:50:27'18.0'Apple Music'18.0YesNoNoEDMYesNo90.0SometimesRarely'Very frequently'NeverRarelySometimesSometimesNeverNeverSometimesSometimesRarelySometimesSometimesSometimesSometimes9.08.05.010.0Improve'I understand.'
727'10/26/2022 19:45:54'26.0'YouTube Music'1.0YesNoNoMetalYesYes136.0SometimesRarelySometimes'Very frequently'NeverNeverRarelyNeverNeverRarely'Very frequently'RarelyNeverNeverNeverRarely0.00.00.00.0'No effect''I understand.'
728'10/30/2022 7:24:08'14.0'Other streaming service'7.0YesYesNoCountryYesNo108.0Rarely'Very frequently'SometimesSometimes'Very frequently'SometimesNeverNeverNeverRarelySometimes'Very frequently'SometimesSometimes'Very frequently'Rarely7.03.01.02.0Improve'I understand.'
729'10/30/2022 13:13:32'21.0'I do not use a streaming service.'0.5NoNoNoPopYesNo95.0NeverRarelySometimesNeverNeverSometimesRarelySometimesNever'Very frequently'Never'Very frequently'SometimesSometimes'Very frequently'Never6.02.02.00.0Improve'I understand.'
730'10/30/2022 13:15:26'21.0Spotify2.0YesNoNoR&BYesYes147.0SometimesNeverSometimesRarelyNeverNeverSometimes'Very frequently'NeverSometimesRarelySometimes'Very frequently'SometimesSometimesSometimes7.06.04.06.0Improve'I understand.'
731'10/30/2022 14:37:28'17.0Spotify2.0YesYesNoRockYesYes120.0'Very frequently'RarelyNeverSometimesNeverSometimesRarelyNeverSometimesRarelyRarely'Very frequently'NeverRarely'Very frequently'Never7.06.00.09.0Improve'I understand.'
732'11/1/2022 22:26:42'18.0Spotify1.0YesYesNoPopYesYes160.0RarelyRarelyNeverNeverNeverNeverRarelyNeverNeverRarelyNever'Very frequently'NeverNeverSometimesSometimes3.02.02.05.0Improve'I understand.'
733'11/3/2022 23:24:38'19.0'Other streaming service'6.0YesNoYesRapYesNo120.0RarelySometimesSometimesRarelyRarely'Very frequently'RarelyRarelyRarelySometimesRarelySometimesSometimesSometimesRarelyRarely2.02.02.02.0Improve'I understand.'
734'11/4/2022 17:31:47'19.0Spotify5.0YesYesNoClassicalNoNo170.0'Very frequently'NeverNeverNeverNeverNeverRarelyNeverNeverNeverNeverNeverNeverNeverNeverSometimes2.03.02.01.0Improve'I understand.'
735'11/9/2022 1:55:20'29.0'YouTube Music'2.0YesNoNo'Hip hop'YesYes98.0SometimesRarely'Very frequently'SometimesRarely'Very frequently''Very frequently'SometimesNeverRarelyNeverSometimes'Very frequently''Very frequently''Very frequently'Rarely2.02.02.05.0Improve'I understand.'